This paper sets out the central problem of current blended learning research that it does not have an appropriate focus on educational theory. The blended learning praxis in higher...
Active learning (AL) is getting more and more popular as a methodology to considerably reduce the annotation effort when building training material for statistical learning method...
In this paper, we study the problem of transfer learning from text to images in the context of network data in which link based bridges are available to transfer the knowledge bet...
Discriminative learning methods are widely used in natural language processing. These methods work best when their training and test data are drawn from the same distribution. For...
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...